Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Doctorate or above
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise;Use social media;Watch dance or ballet;Watch sports;Attend football matches;Listen to classical music 
Devices used daily: Smartphone;Laptop 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;GitHub Copilot;Grok;Google Gemini 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Translation;Brainstorming;Generic chatbot conversation;Generate art;Digital content creation (e.g., creation of social media content) 
Contexts of LLM use: Entertainment;Learning;Personal;Creative or artistic;Work 
Prompt 1: 20 ways of addressing conservation of herbal plants challenges in Nigeria
Prompt 2: List 20 Additional insights on the conservation of medical plants in Otukpo metropolis 
Prompt 3: Write a short and brief erotic story 
Prompt 4: Write a short erotic story
Prompt 5: List 20 different Additional insights on the conservation of medical plants in Otukpo metropolis
Prompt 6: Paraphrase the above insight
Prompt 7: List 4  insights each on the conservation of medical plants in Otukpo metropolis for 50 respondents
Prompt 8: Generate 4 insights for 50 respondents each
Prompt 9: Add 42 more groups 
Prompt 10: With your analysis, give me 6 football matches for August 7, 2024 that will end in a full time draw 
Comments: great survey